Abstract
In this paper the authors present the UPC speaker diarization system for the NIST Rich Transcription Evaluation (RT07s) [1] conducted on the conference environment. The presented system is based on the ICSI RT06s system, which employs agglomerative clustering with a modified Bayesian Criterion (BIC) measure to decide which pairs of clusters to merge and to determine when to stop merging clusters [2]. This is the first participation of the UPC in the RT Speaker Diarization Evaluation and the purpose of this work has been the consolidation of a baseline system which can be used in the future for further research in the field of diarization. We have introduced, as prior modules before the diarization system, an Speech/Non-Speech detection module based on a Support Vector Machine from UPC and a Wiener Filtering from an implementation of the QIO front-end. In the speech parameterization a Frequency Filtering (FF) of the filter-bank energies is applied instead the classical Discrete Cosine Transform in the Mel-Cepstrum analysis. In addition, it is introduced a small changes in the complexity selection algorithm and a new post-processing technique which process the shortest clusters at the end of each Viterbi segmentation.
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Luque, J., Anguera, X., Temko, A., Hernando, J. (2008). Speaker Diarization for Conference Room: The UPC RT07s Evaluation System. In: Stiefelhagen, R., Bowers, R., Fiscus, J. (eds) Multimodal Technologies for Perception of Humans. RT CLEAR 2007 2007. Lecture Notes in Computer Science, vol 4625. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68585-2_50
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DOI: https://doi.org/10.1007/978-3-540-68585-2_50
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